Instructions to use OrionZheng/openmoe-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OrionZheng/openmoe-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OrionZheng/openmoe-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OrionZheng/openmoe-base", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("OrionZheng/openmoe-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OrionZheng/openmoe-base with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OrionZheng/openmoe-base" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OrionZheng/openmoe-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OrionZheng/openmoe-base
- SGLang
How to use OrionZheng/openmoe-base with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "OrionZheng/openmoe-base" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OrionZheng/openmoe-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "OrionZheng/openmoe-base" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OrionZheng/openmoe-base", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OrionZheng/openmoe-base with Docker Model Runner:
docker model run hf.co/OrionZheng/openmoe-base
Update colab_env.txt
Browse files- colab_env.txt +1 -1
colab_env.txt
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@@ -16,7 +16,7 @@ tensorflow-cpu==2.15.0.post1
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tensorstore==0.1.45
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protobuf==3.20.3
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colossalai >= 0.3.3
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torch >=
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transformers==4.34.0
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sentencepiece==0.1.99
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datasets==2.14.7
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tensorstore==0.1.45
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protobuf==3.20.3
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colossalai >= 0.3.3
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+
torch >= 2.1.0
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transformers==4.34.0
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sentencepiece==0.1.99
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datasets==2.14.7
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